| adaptive.density {spatstat.explore} | R Documentation |
Adaptive Estimate of Intensity of Point Pattern
Description
Computes an adaptive estimate of the intensity function of a point pattern.
Usage
adaptive.density(X, ..., method=c("voronoi","kernel", "nearest"))
Arguments
X |
Point pattern (object of class |
method |
Character string specifying the estimation method |
... |
Additional arguments passed to
|
Details
This function is an alternative to density.ppp
and density.lpp. It
computes an estimate of the intensity function of a point pattern
dataset. The result is a pixel image giving the estimated intensity.
If method="voronoi" the data are passed to the function
densityVoronoi which estimates the intensity using
the Voronoi-Dirichlet tessellation.
If method="kernel" the data are passed to the function
densityAdaptiveKernel.ppp which estimates the intensity
using a variable-bandwidth kernel estimator. (This is not yet supported
when X has class "lpp".)
If method="nearest" the data are passed to the function
nndensity.ppp which estimates the intensity using the
distance to the k-th nearest data point. (This is not yet supported
when X has class "lpp".)
Value
A pixel image (object of class "im" or "linim")
whose values are estimates of the intensity of X.
Author(s)
Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner rolfturner@posteo.net and Ege Rubak rubak@math.aau.dk and Mehdi Moradi m2.moradi@yahoo.com.
See Also
density.ppp,
densityVoronoi,
densityAdaptiveKernel.ppp,
nndensity.ppp,
im.object.
Examples
plot(adaptive.density(nztrees, 1), main="Voronoi estimate")